Member of Technical Staff, Senior AI Infrastructure Engineer

About Us

Edison Scientific builds and deploys AI scientist agents to accelerate science and the development of new medicines. We are an ambitious team run by scientists and engineers from leading institutions across biology, physics, chemistry, and AI.

About the Role

As a Senior Member of Technical Staff, Infrastructure Engineer, you'll play a key role in designing, scaling, and operating the core platform infrastructure that powers autonomous scientific discovery. Our mission is to build an AI scientist, and you'll own the infrastructure foundation it runs on. AI agents performing long-running scientific research demand resilient scheduling, lifecycle management, and resource orchestration far beyond typical cloud-native workloads. This role will establish infrastructure best practices, and partner closely with backend engineers, ML engineers, and researchers to deliver a production-grade environment that lets science move faster.

Key Responsibilities

• Build, maintain, and improve Kubernetes-based infrastructure that supports agent workloads, research services, and internal platforms.

• Contribute to cluster scaling, resource management, and operational improvements as platform usage grows.

• Develop and maintain infrastructure tooling, automation, and deployment workflows that improve reliability and developer productivity.

• Help implement monitoring, observability, and alerting systems to ensure platform health and performance.

• Support storage, networking, and security initiatives within our Kubernetes environments.

• Troubleshoot infrastructure and production issues across distributed systems and participate in incident response efforts.

• Collaborate with backend, ML, and research teams to understand workload requirements and implement reliable infrastructure solutions.

• Contribute to infrastructure best practices, documentation, and operational processes.

Required Qualifications

• 6+ years of software, infrastructure, platform, or DevOps engineering experience.

• Experience working with Kubernetes in development or production environments.

• Familiarity with cloud platforms such as AWS, GCP, or Azure.

• Proficiency in at least one programming language such as Python, Go, Java, or TypeScript.

• Experience with infrastructure-as-code tools such as Terraform, Pulumi, or similar technologies.

• Understanding of containerized applications, networking fundamentals, and distributed systems concepts.

• Experience using CI/CD pipelines, version control systems, and automated testing practices.

• Ability to work independently while collaborating effectively across teams.

• Curiosity, strong problem-solving skills, and a desire to learn new technologies.

Preferred Qualifications

• Security like experience with gvisor/kata containers, snapshots

Why join us?

We're a fast-moving, mission-driven culture where smart people do their best work and actually enjoy doing it. We also offer full-time employees the following:

• Competitive salary and equity

• Full healthcare coverage; we pay 100% of premiums for you and your dependents

• Support for growing families, including a yearly new parent stipend and fertility coverage through Carrot

• Mental health support through Rula, our in-network therapist and psychiatrist network with fast availability

• 12 weeks of paid parental leave for maternity, paternity, and adoption

• Pet care support with a yearly employer-funded stipend for your animal companions

• Commuter benefits so you can pay for transit and parking with pre-tax dollars

• 401(k) company matching

• $300 health and wellness benefit quarterly

• Lunch is on us every day you're in the office, and dinner is on us when you're working late

• Regular team off-sites and company events

Edison Scientific is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic under applicable law.